add script to extract perfusion values from polar maps

mu_map/data/get_perfusion_scores.py

+from dataclasses import dataclass
+from typing import Tuple
+
+import cv2 as cv
+import numpy as np
+import pytesseract
+
+
+@dataclass
+class PolarMapSegment:
+    id: int
+    rect: Tuple[int, int, int, int]
+    name: str
+    location: str
+
+
+# see https://www.ahajournals.org/doi/full/10.1161/hc0402.102975
+SEGMENTS = [
+    PolarMapSegment( id=1,  location="basal",      name="anterior", rect=( 14, 190,  41, 217)),
+    PolarMapSegment( id=2,  location="basal",  name="anteroseptal", rect=(101,  36, 128,  63)),
+    PolarMapSegment( id=3,  location="basal",  name="inferoseptal", rect=(277,  36, 304,  63)),
+    PolarMapSegment( id=4,  location="basal",      name="inferior", rect=(365, 190, 392, 217)),
+    PolarMapSegment( id=5,  location="basal", name="inferolateral", rect=(277, 341, 304, 370)),
+    PolarMapSegment( id=6,  location="basal", name="anterolateral", rect=(101, 340, 128, 367)),
+    PolarMapSegment( id=7,    location="mid",      name="anterior", rect=( 64, 190,  91, 217)),
+    PolarMapSegment( id=8,    location="mid",  name="anteroseptal", rect=(128,  80, 155, 107)),
+    PolarMapSegment( id=9,    location="mid",  name="inferoseptal", rect=(251,  80, 278, 107)),
+    PolarMapSegment(id=10,    location="mid",      name="inferior", rect=(313, 188, 340, 215)),
+    PolarMapSegment(id=11,    location="mid", name="inferolateral", rect=(251, 298, 278, 325)),
+    PolarMapSegment(id=12,    location="mid", name="anterolateral", rect=(128, 298, 155, 325)),
+    PolarMapSegment(id=13, location="apical",      name="anterior", rect=(115, 190, 142, 217)),
+    PolarMapSegment(id=14, location="apical",        name="septal", rect=(190, 113, 217, 140)),
+    PolarMapSegment(id=15, location="apical",      name="inferior", rect=(265, 188, 292, 215)),
+    PolarMapSegment(id=16, location="apical",       name="lateral", rect=(190, 265, 217, 292)),
+    PolarMapSegment(id=17,   location="apex",          name="apex", rect=(190, 190, 217, 217)),
+]
+
+
+hsv_green_lower = np.array([40, 100, 100])
+hsv_green_upper = np.array([80, 255, 255])
+
+
+if __name__ == "__main__":
+    import argparse
+    import os
+
+    import pandas as pd
+
+    from mu_map.data.prepare_polar_maps import headers
+
+    parser = argparse.ArgumentParser(
+        formatter_class=argparse.ArgumentDefaultsHelpFormatter,
+    )
+    parser.add_argument(
+        "--polar_map_dir", type=str, required=True, help="directory where files are output to"
+    )
+    parser.add_argument(
+        "--images_dir",
+        type=str,
+        default="images",
+        help="directory under <out_dir> where images of polar maps are stored",
+    )
+    parser.add_argument(
+        "--csv",
+        type=str,
+        default="polar_maps.csv",
+        help="file unter <out_dir> where meta information is stored",
+    )
+    parser.add_argument(
+        "--perfusion_csv",
+        type=str,
+        default="perfusion.csv",
+        help="csv file output by this script under polar_map_dir",
+    )
+    parser.add_argument(
+        "--number_res",
+        type=int,
+        default=128,
+        help="numbers cutouts are rescaled to this resolution for better number recognition",
+    )
+    args = parser.parse_args()
+
+    args.images_dir = os.path.join(args.polar_map_dir, args.images_dir)
+    args.csv = os.path.join(args.polar_map_dir, args.csv)
+    args.perfusion_csv = os.path.join(args.polar_map_dir, args.perfusion_csv)
+
+    data = pd.read_csv(args.csv)
+    rows = []
+    for i in range(len(data)):
+        row = data.iloc[i]
+        _id = row[headers.id]
+        _file = os.path.join(args.images_dir, row[headers.file])
+
+        polar_map = cv.imread(_file)
+        for segment in SEGMENTS:
+            # extract number segment
+            top, left, bottom, right = segment.rect
+            img_number = polar_map[top:bottom, left:right]
+
+            # process segment for improved automatic number detection
+            img_number = cv.resize(img_number, (args.number_res, args.number_res))
+            img_number = cv.cvtColor(img_number, cv.COLOR_BGR2HSV)
+            img_number = cv.inRange(img_number, hsv_green_lower, hsv_green_upper)
+            img_number = cv.morphologyEx(img_number, cv.MORPH_CLOSE, np.ones((4, 4), np.uint8))
+            img_number = cv.morphologyEx(img_number, cv.MORPH_OPEN, np.ones((2, 2), np.uint8))
+            _, img_number = cv.threshold(img_number, 0, 255, cv.THRESH_BINARY_INV)
+
+            # try to recognize number
+            str_number = pytesseract.image_to_string(img_number, config="-c tessedit_char_whitelist=[1,2,3,4,5,6,7,8,9,0] --psm 7")
+            str_number = str_number.strip()
+
+            # prepare image for visualization
+            _polar_map = polar_map.copy()
+            _polar_map = cv.rectangle(_polar_map, (left, top), (right, bottom), (255, 255, 255), 1)
+            _polar_map = cv.resize(_polar_map, (512, 512))
+            img_number = img_number.repeat(3).reshape((*img_number.shape, 3))
+            img_number = cv.resize(img_number, (512, 512))
+            space_h = np.full((512, 10, 3), 239, np.uint8)
+
+            cv.imshow("Polar Map - Segment", np.hstack((_polar_map, space_h, img_number)))
+            cv.waitKey(50)
+
+            while True:
+                _input = input(f"Number is {str_number} (y/other): ")
+                try:
+                    if _input == "y":
+                        number = int(str_number)
+                        break
+                    elif _input == "q":
+                        exit(0)
+                    else:
+                        number = int(_input)
+                        break
+                except ValueError:
+                    print(f"Cannot parse {_input} as a number. Please enter a valid number.")
+
+            _value = pd.Series({f"segment_{segment.id}": number})
+            row = pd.concat([row, _value])
+        rows.append(row)
+    pd.DataFrame(rows).to_csv(args.perfusion_csv)
+
+